Self-tuning personalized information retrieval in an ontology-based framework

Castells, P; Fernandez, M; Vallet, D; Mylonas, P; Avrithis, Y

dc.contributor.author	Castells, P	en
dc.contributor.author	Fernandez, M	en
dc.contributor.author	Vallet, D	en
dc.contributor.author	Mylonas, P	en
dc.contributor.author	Avrithis, Y	en
dc.date.accessioned	2014-03-01T02:43:31Z
dc.date.available	2014-03-01T02:43:31Z
dc.date.issued	2005	en
dc.identifier.issn	0302-9743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31454
dc.subject	Domain Ontology	en
dc.subject	Information Retrieval	en
dc.subject	User Preferences	en
dc.subject.classification	Computer Science, Theory & Methods	en
dc.subject.other	Adaptive systems	en
dc.subject.other	Automation	en
dc.subject.other	Computer systems	en
dc.subject.other	Information technology	en
dc.subject.other	Reliability	en
dc.subject.other	Semantics	en
dc.subject.other	Ontology-based retrieval systems	en
dc.subject.other	Personalization frameworks	en
dc.subject.other	Personalization technologies	en
dc.subject.other	Semantic-based personalization techniques	en
dc.subject.other	Information retrieval	en
dc.title	Self-tuning personalized information retrieval in an ontology-based framework	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/11575863_119	en
heal.identifier.secondary	http://dx.doi.org/10.1007/11575863_119	en
heal.language	English	en
heal.publicationDate	2005	en
heal.abstract	Reliability is a well-known concern in the field of personalization technologies. We propose the extension of an ontology-based retrieval system with semantic-based personalization techniques, upon which automatic mechanisms are devised that dynamically gauge the degree of personalization, so as to benefit from adaptivity but yet reduce the risk of obtrusiveness and loss of user control. On the basis of a common domain ontology KB, the personalization framework represents, captures and exploits user preferences to bias search results towards personal user interests. Upon this, the intensity of personalization is automatically increased or decreased according to an assessment of the imprecision contained in user requests and system responses before personalization is applied. © Springer-Verlag Berlin Heidelberg 2005.	en
heal.publisher	SPRINGER-VERLAG BERLIN	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
heal.bookName	LECTURE NOTES IN COMPUTER SCIENCE	en
dc.identifier.doi	10.1007/11575863_119	en
dc.identifier.isi	ISI:000233744700120	en
dc.identifier.volume	3762 LNCS	en
dc.identifier.spage	977	en
dc.identifier.epage	986	en